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CuSha is a CUDA-based vertex-centric graph processing framework that uses G-Shards and CW representations.
SoCC'20 and TPDS'21: Scaling GNN Training on Large Graphs via Computation-aware Caching and Partitioning.
a fast graph database system on CPU/GPU platforms
High-performance CUDA C++ implementation of Graph Convolutional Networks
a parallelized GCN model implemented with pure C++
Approximate Graph Propagation
yuxin370 / postgres
Forked from postgres/postgresMirror of the official PostgreSQL GIT repository. Note that this is just a *mirror* - we don't work with pull requests on github. To contribute, please see https://wiki.postgresql.org/wiki/Submitti…
A FPGA friendly 32 bit RISC-V CPU implementation
[SIGMOD'23] Data Stream Clustering: An In-depth Empirical Study [ICDM'24] MOStream: A Modular and Self-Optimizing Data Stream Clustering Algorithm
A curated list of deep learning resources for video-text retrieval.
Pytorch implementation of Supporting Clustering with Contrastive Learning, NAACL 2021
mimalloc is a compact general purpose allocator with excellent performance.
A new markup-based typesetting system that is powerful and easy to learn.
A repository that stores some relative mathematical modeling materials, notes, and web sites
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch:入门与实战》)
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